• Journal of KIISE:Software and Applications
• /
• v.28 no.9
• /
• pp.681-687
• /
• 2001

In order to raise a class discrimination power by combining multiple classifiers under the Bayesian decision theory, the upper bound of a Bayes error rate bounded by the conditional entropy of a class variable and decision variables obtained from training data samples should be minimized. Wang and Wong proposed a tree dependence first-order approximation scheme of a high order probability distribution composed of the class and multiple feature pattern variables for minimizing the upper bound of the Bayes error rate. This paper presents an extended high order product approximation scheme dealing with higher order dependency more than the first-order tree dependence, based on the minimization of the upper bound of the Bayes error rate. Multiple recognizers for unconstrained handwritten numerals from CENPARMI were combined by the proposed approximation scheme using the Bayesian formalism, and the high recognition rates were obtained by them.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.14 no.2
• /
• pp.89-95
• /
• 2003

This paper proposes downlink blocking model and approximation equation using lower bound approximation in order to determine the proper guard band between cdma2000 1X and WCDMA in handover areas. The frequency sharing conditions obtained by the model and approximation equation on blocking probability proposed in the paper, are co-site of base station and guard band higher than 1 MHz. Also, the proposed equation is in the form of Q-function. It is an analytical solution overcoming the drawback of recalculation, belonged to Monte-Carlo technique.

• Korean Journal of Computational Design and Engineering
• /
• v.15 no.2
• /
• pp.115-123
• /
• 2010

We present an efficient algorithm for computing the Hausdorff distance between two planar curves. The algorithm is based on an efficient trimming technique that eliminates the curve domains that make no contribution to the final Hausdorff distance. The input curves are first approximated with biarcs within a given error bound in a pre-processing step. Using the biarc approximation, the distance map of an input curve is then approximated and stored into the graphics hardware depth-buffer by rendering the distance maps (represented as circular cones) of the biarcs. We repeat the same procedure for the other input curve. By sampling points on each input curve and reading the distance from the other curve (stored in the hardware depth-buffer), we can easily estimate a lower bound of the Hausdorff distance. Based on the lower bound, the algorithm eliminates redundant curve segments where the exact Hausdorff distance can never be obtained. Finally, we employ a multivariate equation solver to compute the Hausdorff distance efficiently using the remaining curve segments only.

• Journal of Institute of Control, Robotics and Systems
• /
• v.14 no.10
• /
• pp.1014-1021
• /
• 2008

This paper proposes an intelligent sliding mode control method for robotic systems with the unknown bound of model uncertainties. In our control structure, the unknown bound of model uncertainties is used as the gain of the sliding controller. Then, we employ the function approximation technique to estimate the unknown nonlinear function including the width of boundary layer and the uncertainty bound of robotic systems. The adaptation laws for all parameters of the self-recurrent wavelet neural network and those for the reconstruction error compensator are derived from the Lyapunov stability theorem, which are used for an on-line control of robotic systems with model uncertainties and external disturbances. Accordingly, the proposed method can not only overcome the chattering phenomenon in the control effort but also have the robustness regardless of model uncertainties and external disturbances. Finally, simulation results for the five-link biped robot are included to illustrate the effectiveness of the proposed method.

• Journal of KIISE:Computer Systems and Theory
• /
• v.30 no.7_8
• /
• pp.387-396
• /
• 2003

This paper provides an approximation algorithm for STP-MSP(Steiner Tree Problem with minimum number of Steiner Points).Because it seems to be impossible to have a PTAS(Polynomial Time Approximation Schemes), which gives the near optimal solutions, for the problem, the algorithm of this paper is an alternative that has the approximation ratio 2 with $n^{O(1)}$ run time. The importance of this paper is the potential to solve other related unsolved problems. The idea of this paper is to distribute the error allowance over the problem instance so that we may reduce the run time to polynomial bound out of infinitely many cases. There are earlier works[1,2] that show the approximations that have practical run times with the ratio of bigger than 2, but this paper shows the existence of a poly time approximation algorithm with the ratio 2.

• Nuclear Engineering and Technology
• /
• v.54 no.8
• /
• pp.2933-2940
• /
• 2022

Approximations such as the delete-term approximation, rare event approximation, and minimal cutset upper bound (MCUB) need to be prudently applied for the quantification of a seismic probabilistic safety assessment (PSA) model. Important characteristics of seismic PSA models indicate that preserving the success branches in a primary seismic event tree is necessary. Based on the authors' experience in modeling and quantifying plant-level seismic PSA models, the effects of applying negate-down to the success branches in primary seismic event trees on the quantification results are summarized along with the following three insights gained: (1) there are two competing effects on the MCUB-based quantification results: one tending to increase and the other tending to decrease; (2) the binary decision diagram does not always provide exact quantification results; and (3) it is identified when the exact results will be obtained, and which combination provides more conservative results compared to the others. Complicated interactions occur in Boolean variable manipulation, approximation, and the quantification of a seismic PSA model. The insights presented herein can assist PSA analysts to better understand the important theoretical principles associated with the quantification of seismic PSA models.

• Management Science and Financial Engineering
• /
• v.16 no.1
• /
• pp.81-117
• /
• 2010

Semi-supervised learning incorporates unlabeled examples, whose labels are unknown, as well as labeled examples into learning process. Although transductive support vector machine (TSVM), one of semi-supervised learning models, was proposed about a decade ago, its application to large-scaled data has still been limited due to its high computational complexity. Our previous research addressed this limitation by introducing a branch-and-bound algorithm for finding an optimal solution to TSVM. In this paper, we propose three new techniques to enhance the performance of the branch-and-bound algorithm. The first one tightens min-cut bound, one of two bounding strategies. Another technique exploits a graph-based approximation to a support vector machine problem to avoid the most time-consuming step. The last one tries to fix the labels of unlabeled examples whose labels can be obviously predicted based on labeled examples. Experimental results are presented which demonstrate that the proposed techniques can reduce drastically the number of subproblems and eventually computational time.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.21 no.8
• /
• pp.1218-1228
• /
• 1997

The move limit strategy is used to avoid the excessive approximation in the structural optimization. The size of move limit has been obtained by engineering experience. Recently, efforts based on analytic methods are performed by some researchers. These methods still have problems, such as prematurity or oscillation of the move limit size. The existing methods usually control the bound of design variables based on the magnitude. Thus, they can not properly handle the configuration variables based on the geometry in the configuration optimization. In this research, the size of move limit is calculated based on the accuracy of approximation. The method is coded and applied to the two-point reciprocal quadratic approximation method. The efficiency is evaluated through examples.

• Journal of Institute of Control, Robotics and Systems
• /
• v.4 no.2
• /
• pp.170-177
• /
• 1998

In this paper, a unified solution of Hankel norm approximation problem is proposed by $\delta$-operator. To derive the main result, all-pass property is derived from the inner and co-inner property in the $\delta$-domain. The solution of all-pass becomes an optimal Hankel norm approximation problem in .delta.-domain through LLFT(Low Linear Fractional Transformation) inserting feedback term $\phi(\gamma)$, which is a free design parameter, to hold the error bound desired against the variance between the original model and the solution of Hankel norm approximation problem. The proposed solution does not only cover continuous and discrete ones depending on sampling interval but also plays a key role in robust control and model reduction problem. The verification of the proposed solution is exemplified via simulation for the zero-order Hankel norm approximation problem and the model reduction problem applied to a 16th order MIMO system.

• International Journal of Reliability and Applications
• /
• v.13 no.2
• /
• pp.71-80
• /
• 2012

This paper introduces a new approach for evaluating reliability of a complex system in terms of distributional parameters where analytical determination of reliability is intractable. The concept of discrete approximation, reported in the literature so far, fails to meet the latter requirement in terms of distributional parameters. The current work aims at offering a bound based approach where reliability planners not only get a clear idea about the extent of error but also can manipulate in terms of distributional parameters. This reliability approximation has been under taken under the Weibull frame work which is the most widely used model for reliability analysis. Numerical study has been carried out to examine the strength of our proposed reliability approximation via closeness between the two reliability bounds. This approach will be very useful during the early stages of product design as the distributional parameters can be adjusted.